License Plate Recognition
License Plate Recognition (LPR), also known as Automatic Number Plate Recognition (ANPR), is a method, known for those versed in the art, for automatically reading a vehicle registration string off a license plate. An imaging system used for LPR uses a camera to capture one or more images of the front and/or rear license plates while it should be appreciated that each image potentially contains information relating to the license plate. A license plate includes alphanumeric characters and/or possibly other signs, forming the registration string and used for vehicle recognition. In order to allow automatic recognition of the registration string it may be desired to increase the contrast between the license strings' signs and their background, hence the LPR system normally employs illumination units, which are either based on constant lighting or pulsed illumination.
Those versed in the art know that alphanumeric characters can be scanned and processed via an Optical Character Recognition (OCR) process. An OCR process is described, e.g., in US 2008/0131001 (“Multi level Neural Network based characters Identification Method and system”, Hofman and Margolin, published on 2008), describing a system and a method, which enable automatic identification of characters while performing and calibrating data verification to ensure data reliability. The system described in US 2008/0131001 can process these identified characters, such as override adverse conditions, adjusting and correcting unclear characters and their images.
Factors Affecting Recognition Success
LPR systems require high level of accuracy as well as reports on the confidence of the results. Error in the recognition process may cause undesired consequences, such as billing wrong drivers (in toll roads), launching security forces due to wrong recognition of a vehicle (in security systems), preventing access from an authorized vehicle (in gates), and so on. Therefore it is important to employ special techniques that increase the accuracy and prevent recognition errors.
It is possible to categorize the success of an LPR process based on a number of parameters and factors, constituting “affecting parameters”, including internal factors, plate complexity, external factors, plate make and condition:                Internal factors include, e.g., the quality of the LPR program, the resolution and quality of the camera, the quality and type of illumination, the field of view.        Plate complexity includes, for example, the possible combinations of the legal alphanumeric strings, presence of graphics and special symbols, the use of multiple rows or staggered letters, use of abnormal font types, use of colors, etc.        External factors include parameters such as environmental parameters (indicative, for example, of the sun's intensity and radiation, glare, rain, fog, etc.) and parameters relating to the vehicle (such as the speed of the vehicle, etc.).        The condition of the plate is affected, e.g., by obscuring elements—such as vehicle hooks, license frames, screws and dents.        The plate make depends, for example, on the quality of the paint, whether the plate is retro-reflective or reflective, the contrast and colors of the alphanumeric characters and their background.        
Efforts have been done, in the past, to cope with these factors or with part thereof. For example, U.S. Pat. No. 6,650,765 (“System for simultaneously imaging vehicles and their license plate”, Alves, published on 2001), describes a vehicle video imaging system that comprises a white-light LED array for illuminating retro-reflective painted parts of a vehicle's license plate, a powerful flash with a visual spectrum cutout filter and a polarizing filter for illuminating any non-retro-reflective license plate paint and the vehicle itself. A video camera with a polarizing filter turned 90 degree relative to the one in front of the flash receives the illuminated image of the vehicle and its license plate. The retro-reflective paint of a license plate will return polarized light as it is received, so the white-light LED array will provide all the illumination needed by the camera to get a good high-contrast picture of the license plate. The polarizing filters will combine to block out most of the light from the flash that was returned still-polarized by the retro-reflective-paint license plate. All other surfaces that do not have retro-reflective paint will bounce-back and scatter the light from both the polarized flash and non-polarized light.
Contrast Enhancement
Amongst the steps of OCR are segmentation of the alphanumeric characters (detecting each character position) and identification of each character. During these steps the contrast of the characters in relation to their background is an important factor, assisting in differentiating the characters from their background. Acceptably, around 20% contrast provides satisfactory results in the ability of separating the characters and identifying them correctly. However, due to the affecting parameters described above the images obtained from the cameras may suffer from low differentiation. Although the OCR process can attempt to increase the contrast using various known pre-se methods such as histogram modification, the input quality is a limiting factor that drives the overall results to lower recognition rates and prevents repeatability of the results.
There are known optical contrast enhancement techniques, such as illuminating the license plate with a narrow spectrum, for example near-infrared (near-IR), which is different from the color of the characters and/or the background. Additionally or alternatively, it is possible to use an optical band pass filter in the optical path between the camera and the license plate in order to filter out light in other spectrums. The resulting image is expected to have higher character contrast, which may improve the OCR results.
Presently, many LPR systems use near-IR spectrum as their preferred spectrum, since the driver cannot see this bandwidth and thus, a high level of illumination may be used without affecting the driver. Typical spectrums include, e.g., 850 nM, 880 nM or 950 nM. This spectrums' range (near infrared, shortly denoted “near-IR”) also has acceptable results in outdoor installations.
For example, U.S. Pat. No. 5,591,972 (“Apparatus for reading optical information”, Noble et al., published on 1997) discloses an apparatus for illuminating a distant object such as a vehicle license plate, and for reading optical information on the distant object. The apparatus is a unit which includes a radiation source for illuminating a selected area of the object and a CCD camera for receiving radiation from the object and for producing an electrical signal representative of optical information on the object. The radiation source is coaxial with an imaging lens of the camera and includes arrays of LED's spaced around an optical axis passing through the imaging lens. The LED's emit radiation in the near infrared region and are strobed at a predetermined frequency during the acquisition of the information.
One problem of using near-IR spectrum in an LPR implementation is that in some places, such as Massachusetts (in United States) or Belgium (in Europe), license plates make use of red color, either for the license plate background or for the characters. For such plates, the use of near-IR spectrum results in a low contrast, since the background of the plate is illuminated with the same color of the characters (or opposite: the characters are illuminated with the background color). Therefore, LPR systems for such plates require a different spectrum, probably in the visible range, such as yellow (e.g., 590 nM), which results in improved contrast.
Furthermore, in many cases different license plates exist in the same place and on the same time. Hence, many LPR installations have to cope with such mixed-plates situation, e.g., by having a stereo system using dual spectrums—such as a combination of near-IR and visible color. Each spectrum provides a respective image while it is possible to select the best image out of multiple spectrums. Such LPR systems use two cameras—one with near-IR filter and illumination, and the other with a visible color such as yellow.
In the stereo systems, each camera is often used for capturing multiple images, each image is captured using a different illumination level, wherein one image is selected out of the series of images, and the confidence of the reported result is determined based on the repetition and quality of the recognitions.
Another feature of the presently existing stereo-systems using dual spectrum solution is to allow video motion detection (VMD) to operate in covert IR mode, wherein firing the visible illumination is done a brief moment after the vehicle is detected.
Yet, there is a need in the art for compact, non-expensive modules for acquiring images of car license plates.